https://github.com/dwija12903/password-strength-checker

A Model to evaluate the strength of passwords and enhance security for your applications.
https://github.com/dwija12903/password-strength-checker

matplotlib pandas scikit-learn seaborn xgboost

Last synced: 26 days ago
JSON representation

A Model to evaluate the strength of passwords and enhance security for your applications.

• Host: GitHub
• URL: https://github.com/dwija12903/password-strength-checker
• Owner: dwija12903
• License: mit
• Created: 2024-09-08T22:53:19.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-08T23:04:57.000Z (about 2 months ago)
• Last Synced: 2024-09-30T09:04:20.282Z (about 1 month ago)
• Topics: matplotlib, pandas, scikit-learn, seaborn, xgboost
• Language: Jupyter Notebook
• Homepage:
• Size: 6.14 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
## 🛡️ Password Strength Checker

### 📜 Description

This project is a machine learning model that checks the strength of passwords using the **XGBoost** algorithm. It classifies passwords into three categories: **Weak**, **Moderate**, and **Strong** based on their complexity and security. You can use this model to evaluate the strength of passwords and enhance security for your applications.

### 📊 Dataset

The passwords used in our analysis come from the **000webhost leak** dataset available online, containing more than **6.6 million unique passwords**.

### ✨ Key Features

- **Data Preparation:** Loads and preprocesses password data from a CSV file (`data.csv`).

- **Feature Extraction:** Utilizes `TfidfVectorizer` to convert passwords into numerical features.

- **Model Training:** Applies the **XGBoost** algorithm to classify password strength.

- **Evaluation and Visualization:** Visualizes results using libraries like `matplotlib` and `seaborn`.

### 🛠️ Requirements

- Python 3.9 or higher

- Required libraries: `pandas`, `matplotlib`, `seaborn`, `scikit-learn`, `xgboost`, `dill`

### 🚀 Installation

To run this password strength checker on your local machine, follow these steps:

1. **Clone the Repository:**

   ```bash

   git clone https://github.com/dwija12903/password-strength-checker.git

   cd password-strength-checker

   ```

2. **Install Dependencies:**

   You can install all required libraries by running:

   ```bash

   pip install -r requirements.txt

   ```

3. **Run the Application:**

   To start the application, run:

   ```bash

   python app.py

   ```

### 📈 Usage

1. **Run the Notebook:**

   Open the Jupyter Notebook (`model.ipynb`) and run all cells to train the model and evaluate password strength.

2. **Visualize the Results:**

   The notebook includes plots and visualizations to interpret the model’s performance.

### 📁 Data

The data used for this project is loaded from a CSV file named `data.csv`. This file contains password samples with corresponding labels indicating their strength.

### 🌐 Snippets

![Password Strength Checker](image.png)

##### It was developed as part of academic projects in the Information Security subject. [Report](https://github.com/dwija12903/password-strength-checker/blob/main/Project_Report.pdf)